Exploring the relationship between total serum calcium and melanoma development: a cross-sectional study

Abstract

Background: Melanoma is the fourth leading cause of cancer-related death worldwide. The continuous exploration and reporting of risk factors of melanoma is important for standardizing and reducing the incidence of the disease. Calcium signaling is a promising therapeutic target for melanoma; however, the relationship between total serum calcium levels and melanoma development remains unclear.

Methods: In this study, we included patients with melanoma from the National Health and Nutrition Examination Survey (NHANES) database from 2003 to 2006 and from 2009 to 2016. The baseline clinical characteristics of the participants were analyzed using the chi-square and rank-sum tests. Subsequently, a fitted model was constructed to evaluate the relationship between total serum calcium levels and melanoma development. The performance of total serum calcium levels and covariates in predicting the risk of melanoma was assessed based on ROC curves. Finally, LASSO regression analysis was performed using the "glmnet" R package to identify clinical characteristics associated with melanoma.

Results: A total of 13,432 participants were included in this study. Age, race, household poverty-to-income ratio, response of the skin to sunlight after a certain period of non-exposure, wearing long-sleeved shirts, frequency of sunscreen use, and arthritis were significantly correlated with the development of melanoma. The p-values of total serum calcium levels in three fitted models were < 0.05, and the OR values were < 1. According to the ROC curves, the AUC values of models 2 and 3 were 0.728 and 0.766, respectively, indicating that the combination of total serum calcium levels and covariates showed better performance in predicting the occurrence of melanoma. Furthermore, LASSO regression analysis revealed seven clinical characteristics significantly associated with melanoma.

Conclusion: This study revealed a relationship between total serum calcium levels and melanoma development. Total serum calcium levels combined with phenotypic and clinical characteristics were found to be more effective in predicting the occurrence of melanoma. Therefore, the relationship between total serum calcium levels and melanoma development warrants further investigation in prospective cohort studies.

Keywords: LASSO; NHANES; cross-sectional study; melanoma; total serum calcium.

Figure 1

Risk ratios in model 2. Model 2 was adjusted for age, sex, household poverty-to-income ratio, education level, and body mass index based on model 1, and model 3 further incorporated drinking status, smoking status, response of the skin to sunlight after non-exposure, staying in shadows, wearing long-sleeved shirts, frequency of sunscreen use, sunburn, high cholesterol levels, arthritis, chronic bronchitis, diabetes, and high blood pressure.

Figure 2

Risk ratios in model 3.

Figure 3

(A–C) ROC curves of the three models. The combination of total serum calcium levels with other covariates showed better performance in predicting the occurrence of melanoma.

Figure 4

(A,B) Results of LASSO regression analysis. LASSO regression analysis correlation plot. The image on the left shows the plot of the penalty term parameter, with the horizontal coordinate representing the log(lambda) value and the vertical coordinate representing the degree of freedom, which represents the cross-validation error. In the actual analysis, it is hoped that the cross-validation of the error of the smallest position, in the figure, the left dashed position is the cross-validation of the smallest error, according to the position (lambda.min) to determine the topmost cross coordinate log(Lambda), the top shows the number of traits, find the optimal log(Lambda) value, find the corresponding trait and its coefficient in the right figure. In the image on the right, the horizontal coordinate represents log(lambda), whereas the vertical coordinate represents the coefficient of the trait (different variables with λ-penalization).